Predictive enrichment strategies for immune-targeted interventions in depression.
Abstract
BACKGROUND: 30% of Major Depression Disorder patients display an immune-mediated subtype, associated with poor response to first-line antidepressant treatments. Immune-targeted augmentation with anti-inflammatory compounds shows promise and may be more effective for the immune-mediated subgroup. For optimal clinical trial designs, we require guidance on the selection of patients who may benefit, the outcome measures that capture the clinical benefits, and the subtype-specific effect sizes per compound. AIM: Identify baseline predictive blood-based and clinical biomarkers, define the optimal outcome measures for immune-targeted interventions, and rank these based on subtype-specific effect sizes. Facilitate science-to-policy translation by integrating research findings into clinical recommendations and predictive enrichment strategies for future clinical trials. APPROACH: I will address these questions through a dual approach, integrating insights (WP3) gained with stratification meta-analyses and individual participant data (of at least n=10 RCTs) (WP1) with the results of our pre-stratified clinical trial (WP2). IMPACT: My project will innovate MDD treatment guidelines and optimise future RCT protocols. This will result in a decreased number of failed RCTs, which will lead to cost-effective benefits and more interest among pharmaceutical industry players. The predictive enrichment strategies can then be used to innovate intervention trials also in other mental disorders.Researcher(s)
- Promoter: De Picker Livia
- Co-promoter: Morrens Manuel
- Fellow: Wessa Céline
Research team(s)
Funding
- FWO
Project type(s)
- Research Project
Predictive enrichment strategies for immune-targeted interventions in depression.
Abstract
BACKGROUND: 30% of Major Depression Disorder patients display an immune-mediated subtype that is associated with poor response to first-line antidepressant treatments. Immune-targeted augmentation with anti-inflammatory compounds shows promise and may be more effective for the immune-mediated subgroup. For optimal clinical trial designs, we require guidance on the selection of patients who may benefit, on the outcome measures that capture the clinical benefits, and the subtype-specific effect sizes per compound. AIM: Identify baseline predictive blood-based and clinical biomarkers to facilitate predictive enrichment strategies for future clinical trials on immune-mediated depression, define the optimal outcome measures for immune-targeted pharmacological interventions, and ranking these based on their subtype-specific effect sizes. APPROACH: I will address these questions through a dual approach, combining insights gained during the preparation of a new RCT with stratification meta-analyses, design harmonisation and machine learning strategies in existing datasets (n=9 RCTs) within an international consortium. IMPACT: My project will optimise future RCT protocols. This will result in a decreased number of failed RCTs, which leads to cost-effective benefits and more interest among pharmaceutical industry players. The predictive enrichment strategies can then be used to innovate intervention trials also in other mental disorders.Researcher(s)
- Promoter: Morrens Manuel
- Fellow: Wessa Céline
Research team(s)
Funding
- BOF
Project type(s)
- Research Project